235 citations · 330 across the 12 of their papers we have counts for
16 papers
Simulator-Refined Diffusion for Radio-Frequency Inverse Design
Jinhao Liang, Jacob K. Christopher, Michael Frei +2
Diffusion models have shown potential in inverse design of printed circuit boards (PCBs), enabling the generation of layouts conditioned on target S-parameters. Despite this promis…
Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning
Tommaso Dreossi, Christopher M. Bryant, Hao Liu +4
Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to single-layer binary-metallization…
3D Environment Modeling for Falsification and Beyond with Scenic 3.0
Eric Vin, Shun Kashiwa, Matthew Rhea +7
We present a major new version of Scenic, a probabilistic programming language for writing formal models of the environments of cyber-physical systems. Scenic has been successfully…
IB-GAN: A Unified Approach for Multivariate Time Series Classification under Class Imbalance
Grace Deng, Cuize Han, Tommaso Dreossi +2
Classification of large multivariate time series with strong class imbalance is an important task in real-world applications. Standard methods of class weights, oversampling, or pa…
Scenic: A Language for Scenario Specification and Data Generation
Daniel J. Fremont, Edward Kim, Tommaso Dreossi +4
We propose a new probabilistic programming language for the design and analysis of cyber-physical systems, especially those based on machine learning. Specifically, we consider the…
A Formalization of Robustness for Deep Neural Networks
Tommaso Dreossi, Shromona Ghosh, Alberto Sangiovanni-Vincentelli +1
Deep neural networks have been shown to lack robustness to small input perturbations. The process of generating the perturbations that expose the lack of robustness of neural netwo…
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
Tommaso Dreossi, Daniel J. Fremont, Shromona Ghosh +4
We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particu…
Scenic: A Language for Scenario Specification and Scene Generation
Daniel J. Fremont, Tommaso Dreossi, Shromona Ghosh +3
We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the pro…
Semantic Adversarial Deep Learning
Tommaso Dreossi, Somesh Jha, Sanjit A. Seshia
Fueled by massive amounts of data, models produced by machine-learning (ML) algorithms, especially deep neural networks, are being used in diverse domains where trustworthiness is…
Counterexample-Guided Data Augmentation
Tommaso Dreossi, Shromona Ghosh, Xiangyu Yue +3
We present a novel framework for augmenting data sets for machine learning based on counterexamples. Counterexamples are misclassified examples that have important properties for r…
Systematic Testing of Convolutional Neural Networks for Autonomous Driving
Tommaso Dreossi, Shromona Ghosh, Alberto Sangiovanni-Vincentelli +1
We present a framework to systematically analyze convolutional neural networks (CNNs) used in classification of cars in autonomous vehicles. Our analysis procedure comprises an ima…
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components
Tommaso Dreossi, Alexandre Donzé, Sanjit A. Seshia
Cyber-physical systems (CPS), such as automotive systems, are starting to include sophisticated machine learning (ML) components. Their correctness, therefore, depends on propertie…
Sapo: Reachability Computation and Parameter Synthesis of Polynomial Dynamical Systems
Tommaso Dreossi
Sapo is a C++ tool for the formal analysis of polynomial dynamical systems. Its main features are: 1) Reachability computation, i.e., the calculation of the set of states reachable…
Falsifying Oscillation Properties of Parametric Biological Models
Thao Dang, Tommaso Dreossi
We propose an approach to falsification of oscillation properties of parametric biological models, based on the recently developed techniques for testing continuous and hybrid syst…
Approximated Symbolic Computations over Hybrid Automata
Alberto Casagrande, Tommaso Dreossi, Carla Piazza
Hybrid automata are a natural framework for modeling and analyzing systems which exhibit a mixed discrete continuous behaviour. However, the standard operational semantics defined…
Hybrid Automata and ε-Analysis on a Neural Oscillator
Alberto Casagrande, Tommaso Dreossi, Carla Piazza
In this paper we propose a hybrid model of a neural oscillator, obtained by partially discretizing a well-known continuous model. Our construction points out that in this case the…